# -- coding: utf-8 --
import mnistData
import tensorflow as tf
mnist = mnistData.read_data_sets("MNIST_data/", one_hot=True)
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784,10]))
b = tf.Variable(tf.zeros([10]))
y = tf.nn.softmax(tf.matmul(x,W) + b)
y_ = tf.placeholder("float", [None,10])
init = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init)

# begin estimate
print "beigin"
correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
print sess.run(accuracy, feed_dict = {x: mnist.test.images, y_: mnist.test.labels})
print 'end'
